This study measured the structural and organizational changes in the knowledge schema of human cognition in response to the learning achieved by 48 students enrolled in the second year of a psychology degree. Two studies were carried out based on the Chronometric Constructive Cognitive Learning Evaluation Model. This article deals only with the first one, which consisted of a conceptual definition task designed in line with the Natural Semantic Network technique. Participants defined ten target concepts with verbs, nouns, or adjectives (definers), and then weighed the grade of the semantic relationship between the definers and the target concepts. The data indicate that the initial knowledge structures had been modified towards the end of the course. The participants’ human cognition schema presented changes in terms of content, organization, and structure. This evidence supports the idea that the acquisition and transformation of the schemata learned in academic environments may be observed through cognitive science indicators.
This chapter presents a comprehensive method of implementing e-assessment in adaptive e-instruction systems. Specifically, a neural net classifier capable of discerning whether a student has integrated new schema-related concepts from course content into her/his lexicon is used by an expert system with a database containing natural mental representations from course content obtained from students and teachers for adapting e-instruction. Mental representation modeling is used to improve student modeling. Implications for adaptive hypermedia systems and hypertext-based instructions are discussed. Furthermore, it is argued that the current research constitutes a new cognitive science empirical direction to evaluate knowledge acquisition based on meaning information.
This study illustrates the application of the Chronometric Constructive Cognitive Learning Evaluation Model to assess learning about human cognition knowledge schema in 48 second-year psychology students (79% females, 21% males). In the first phase, the participants carried out a conceptual definition task based on the Natural Semantic Networks technique. They defined ten target concepts related to the course by using verbs, substantives, adjectives, and pronouns (definers). Participants then rated the grade of relatedness between definers and targets concepts. Subsequently, the present authors carried out a computational simulation with data from the first study. In addition, students participated in a semantic priming experiment. They participated in a lexical decision task. Participants read pairs of words; these pairs were sometimes related by cognition scheme or common association, and sometimes were unrelated. The three tasks were applied at the start of the course and the end. The computational simulation analysis and ANOVA indicated that the initial pattern for conceptual activation had changed at the end of the course. Additionally, the initial chronometric behavior of the human cognition schema of the participants also changed at the end of the course. This evidence supports the idea that cognitive evaluation tools can help assess the schematic behavior patterns induced by academic learning.
Attitudes towards regular school inclusion of people with intellectual disabilities (ID) are affected by factors such as disability severity, educational level, and teacher experience. Nevertheless, the ways that teachers integrate these factors to form inclusion judgments remains unclear. The current paper explores what systematic cognitive algebra rules are used to cognitively integrate this set of inclusion factors by special education teachers and psychology students. To do so, 469 special education teachers and psychology students were asked to take part in two experimental cognitive algebra studies. In each study, participants had to read a set of school inclusion scenarios and rate the probability that a scenario actor with ID could be successfully integrated into a regular school program. To this purpose, factor effects on successful school inclusion and ID related to individuality, situational aspects, and contextual considerations (e.g., school environment, grade level taught) were explored. Results suggested that participants showed attitudes to school inclusion ranking from light to moderate positive values. Situational factors, as well as context factors, were judged to be more significant than other factors in elementary education. These factors were integrated by following a cognitive summative rule. Overall, judgment for successful school inclusion follows a summative rule to integrate sources of information. This rule is maintained irrespective of the disability under consideration. However, valuation of each source of information does depend on the type of the current study sample. Implications of these results for inclusion of people with disabilities in regular schools are discussed in this paper.
Background: This paper aimed to explore the ability of people with Down syndrome (PWDS) in recognizing facial emotion by considering automatic cognitive processing levels of face recognition. Method: A sample of PWDS and participants with typical development (PWTD) participated in a set of two affective priming studies. In each study, participants had to categorize an emotional or neutral target face that was preceded by another emotional face. Stimuli presentation for each facial set (one face after another) was conducted by using an stimulus onset asynchrony (SOA) of 300 ms with the inter-stimulus interval (ISI) set at 50 ms. The first affective priming study manipulated emotion congruency between prime and target emotional faces to explore emotion classification abilities and to identify the cognitive mechanisms underlying automatic recognition of some emotional faces. The second study explored the effect that gender of a face has over categorization of facial emotion and difficulty in recognizing negative facial expressions. Results: The results strongly suggest that not all of the PWDS present difficulties in recognizing negative facial emotions. PWDS' performance pattern in categorizing emotion was similar to that of PWTDs if they had to use broad classification categories (e.g., emotion vs. no emotion). However, differences between both samples occurred if PWDS had to use a specific category task (e.g., classification of happiness, sadness, etc.). Conclusions: At least two emotion information processing styles can be identified in PWDS. Methodological and theoretical implications for exploring the emotional capabilities of people with DS are discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.